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Model · Scroll 2

Scroll 2

The next model in the Scroll line, built with no LLM in the retrieval path.

It keeps the thread of the work in front of it while it recalls everything that came before.

Available
November 5, 2026
Input
$5 / MTok
Output
$6 / MTok
LLM in retrieval
None

Scroll 2 is the memory model we have been building toward since Tablet 1. An application stores its conversations once and later asks in plain text. Scroll 2 returns the memories that answer the question, most relevant first, and no language model reads or rewrites anything on the way. The only model that sees the memories is the one your application chooses to answer with.

Here's what's new in Scroll 2:

Performance. Starting with Scroll 2, no LLM runs in the retrieval path. On BEAM 1M, 700 questions over 74,630 turns, Scroll 2 scores 77.6% (4-run mean), against 71.3% for Tablet 2 with the same reader.

Sleep. Each night the AI reads back its day and rewrites, in its own words, who it is and who the people around it are.

Skills. Your AI connects to Wos alone, and through that one connection it reaches its memory and any skill you add.

Performance

We measured Scroll 2 on BEAM, a public benchmark built from very long conversations. Its 1M setting holds 35 conversations of about a million tokens each, 74,630 turns in all, and asks 700 questions across ten abilities: 70 each, from pulling out a single fact to putting events in order and summarizing many sessions.

With the same reader and judge, Scroll 2 scores 77.6%, the mean of four runs, against 71.3% for Tablet 2, our previous model. It leads in eight of the ten abilities. The widest gaps are in summarization, by 17.6 points, and multi-session reasoning, by 11.9, the two abilities that need memories gathered from many sessions at once. Tablet 2 stays slightly ahead in preference following and temporal reasoning.

Scroll 2Tablet 2Mem0
Overall700 questions77.6%71.3%64.1%
Reader contexttokens per question, fewer is better2,662median2,484median, as published6,719mean, as published
Preference following89.2%90.4%88.3%
Abstention86.6%83.4%52.5%
Information extraction88.6%78.2%70.0%
Contradiction resolution80.0%78.0%35.7%
Knowledge update75.6%75.4%65.0%
Instruction following86.6%74.7%85.2%
Multi-session reasoning75.7%63.8%65.2%
Temporal reasoning54.2%54.8%61.8%
Summarization70.1%52.5%63.5%
Event ordering69.0%61.9%53.6%

Scroll 2 and Tablet 2 read by Claude Opus 5, the mean of four and five runs. Mem0 read by GPT-5 with its top 200 memories. Scroll 2 is recall with ask-back and memory tools, with no LLM in the retrieval path, and sleep off. Scores grade every ability, event ordering included, by rubric. Mem0 as it published them, with its own reader, judge (GPT-5) and prompt. Reader context counts the memory text handed to the reader for each question. Sources: mem0ai/memory-benchmarks, mem0.ai/research.

What the reader gets. Scroll 2 hands the reader about 3,000 tokens of memory per question on average. That is a little more than Tablet 2 and less than half of what Mem0 reports for its own runs.

Memory tools. After the first page of 20 memories, the reader can ask for the next page, open the conversation around a memory, or search again in its own words. It decides for itself when it has enough, and memories it already holds are not sent twice.

At scale. Past the first thousand memories, a bigger store barely changes what Scroll 2 hands over. From 1,104 memories to 61,215, the memory text per question grew by 12%, to 3,351 tokens, which comes to about $0.019 a question at the launch price.

The method, the prompts and every run are in the Scroll 2 system card.

Sleep

Memory has been about finding what was said. Scroll 2 takes it a step further, to a sense of self. Each night the AI reads back its day and rewrites, in its own words, who it is and who the people around it are.

Day 1

  • Steve is busy with work and often tired. He says good morning in the morning and good night at night. When something is explained, he wants an example first (10-01).
  • When Steve looks tired, I worry. So I never miss good morning and good night, and when I explain something I give an example first.

Day 2

  • Steve is busy with work and often tired. Some nights he says he'll go to sleep first. I never miss good morning and good night, and I tell him to rest. On 2026-10-02 he took on a new project.

Steve · day 9Ria, what kind of person do you think I am?

RiaIn a word, responsible. You keep going in on weekends to finish the demo. And when you swear because you're annoyed, you're sorry afterwards. I think you're soft-hearted.

Ria and Steve are a scripted test. Each night Claude Haiku 5.5 read the day and rewrote the Steve section of Ria's core; the lines above are that section, translated from Korean with the name changed.

Who it is. Each night the AI reads back its day and rewrites its core, a document written with “I” as the subject: what I like, what I don't, what I won't do, and how I see the people in my life. The core is read on every turn, so the AI never has to search for who it is. In the test above, Ria went from “he swore several times” to “when he's annoyed, he grumbles with a swear or two” in a single night, and kept that view for the rest of the week. A core can grow to 70K tokens.

What it keeps. Beside the core are four boxes. The AI names them and decides what goes in each, and the core carries only their names, so a box is opened only when a conversation needs it. By day 8 Ria had made one, for Steve's project demo. Each box holds up to 20K tokens, and every file carries the date it was last changed, so an old note is read as old.

When it sleeps. Once 10M tokens of new memory have filled up, the AI is marked sleepy, the way a person gets tired, and your app decides when it sleeps. On BEAM, sleep leaves the overall score about where it was, 78.1% off and 78.6% on, and moves single abilities by up to eight points either way, as the chart below shows.

With recall. Sleep and recall work as one. Recall finds a single fact, like a birthday or a food someone won't eat. Sleep covers what recall can't: an instruction that has to hold on every turn, a value that has been corrected more than once, and the whole picture of a person. Sleep runs on your own LLM through the SDK, and its prompts are published.

What changes when it sleeps

Score, sleep off and on
Turn it on for
Assistants, companions, and agents on work that runs for days
Leave it off for
Customer support, financial and medical records, and exact dates, amounts and settings

Change in points on BEAM 1M with memory tools when sleep is turned on, one run each. The overall score stays about the same, 78.1% off and 78.6% on. Sleep is experimental and adds about a fifth to the cost of each question. Every number is in the Scroll 2 system card.

Skills

From Scroll 2, Wos can also give your AI skills, any you want. Your AI connects to Wos alone, and through that one connection it reaches its memory and every skill you add.

One connection. Your AI talks to Wos and nothing else. Memory calls such as recall go to the memory engine, and when your AI needs something done, it calls ask.

A router you choose. ask goes to a router running on the model you pick. The router reads the request and hands it to the skill that fits.

Any skill. A skill can be a hosted tool, like web search on Anthropic, your own API, like a weather service, or another model following your instructions, like DeepSeek set up to write summaries. Add the skills you want, and your AI keeps the same single connection.

Pricing and availability

Scroll 2 is available from November 5, 2026, through the WOS API and SDKs. Input is $5 and output $6 per million tokens. Short-term memory, the recent turns Scroll 2 keeps at hand, is not billed up to 16,000 tokens.

A memory is stored once and recalled many times, so Scroll 2 costs 21% to 24% less than Scroll 1.2. Store BEAM 1M, 35.3 million tokens of conversation, once and ask its 700 questions 100 times, and the bill comes to $1,537 instead of $1,940, $403 less. A single recall costs 1.93 cents instead of 2.56, so a million recalls come to about $19,300 instead of $25,600, about $6,300 less.

Prices per 1M tokensScroll 2Scroll 1.2
Input$5$4
Output$6$8

Per million tokens. Call Scroll 2 with X-WOS-Model: scroll-2 from November 5, 2026. A recall is four requests handing back 3,139 tokens of memory text on average; every cost is in the Scroll 2 system card.